Birda has spent a lot of time refining the platform in such a way that it produces valuable, quality data for conservation researchers. This is accomplished through a combination of user-centric features as well as background features.
Birda's user-centric features to improve the quality of the sighting data:
When adding sighting records, location-based species lists are used to limit species lists to only the species we know to occur at a location.
When adding sighting records, location-based species lists are also sorted from most common to least common.
Birda's species lists are integrated into the Birda species guide to help users find the correct species when adding sighting records.
Birda has a 'Suggest Species' functionality that gets the community involved in identifying and reviewing species posted.
Birda's community can flag sightings that are incorrectly identified (or have other issues) so that they can be manually reviewed.
Birda is in the process of developing species identification quizzes to track and improve users' species identification skills.
Birda's background features to improve the quality of the sighting data:
Birda uses Birdlife International's bird distribution dataset to verify that sightings have occurred within known distributions and flag sightings occurring outside of known distributions.
Birda uses location-based species lists (based on over 1bn verified historical sighting records) as further verification that sightings have occurred within or outside of known distributions.
Birda is in the process of gauging each user's species identification skills and using this to segregate sightings datasets based on perceived data quality.
Birda is partnering with a variety of local ornithological organisations and ornithologists to vet data and validate unusual records.